Burst suppression (BS) is an electroencephalogram (EEG) pattern typically characterized by low amplitude or suppressed EEG activity punctuated by segments of irregular high amplitude bursts. The presence of BS in EEG recordings has long been identified as indicating acute compromise of brain functioning (Niedermeyer et al., Clin EEG, 1999). Additionally, BS is also observed during the deep stages of general anaesthesia and in conjunction with sedative overdoses, the so-called benign neuropharmacologically-induced BS.
Asphyxia may result in severe brain damage and/or deficits and if so is associated with a poor outcome. Scalp EEG is routinely used to monitor the brain's electrical activity in asphyxic patients and clinicians often assess EEGs in an attempt to reliably and rapidly distinguish between such patients who will benefit from therapeutic intervention, and/or those with a poorer prognosis who may not recover or recover with severe neurological damage and/or deficits.
Following an initial period of quiescence, the EEG from an asphyxic patient typically exhibits BS across most cortical regions of the brain (Niedermeyer et al., Clin EEG, 1999). Individual bursts vary greatly in magnitude and shape, ranging from very brief fluctuations that barely surpass amplifier and physiological noise to high-amplitude waveforms that can last for several seconds. Complete neurological recovery typically occurs only in cases where BS rapidly resolves and normal, continuous EEG activity resumes.
Therefore, a successful clinical outcome depends crucially on the rapid cessation of bursting and the resumption of continuous cortical activity in patients with asphyxia. Despite its importance in the recovery process, mechanisms of BS remain poorly understood, and objective diagnostics are needed to guide clinical decision making including treatment.
By way of example, identification of BS and its recovery time in asphyxic newborns is commonly used as a prognostic indicator of clinical outcome, which may be used to guide clinicians as to who may benefit from maximal care. The interpretation of BS in asphyxic newborns, however, typically only recognizes its presence versus its absence. While a qualitative assessment of “burst sparseness”—a low overall frequency of bursts—may be taken as an additional sign of severity (Walsh, Clin Neurophysiol, 2011), no properties of the bursts themselves have been shown to be useful prognostic indicators. Moreover, while clinical decisions to commence therapeutic hypothermia after birth asphyxia are often based on observing BS in the early EEG, hypothermia treatment itself can significantly delay BS recovery, hence compromising the utility of an early EEG in outcome prediction (Hallberg et al., Acta Paediatrica, 2010).
Bursting activity patterns such as BS represent a pathologically abnormal EEG pattern in neonates. These types of abnormal patterns extend to preterm neonates in which busting patterns also reflect immature cortical development. The transition from BS to discontinuous EEG patterns is also commonly observed. Discontinuous activity patterns have increased levels of bursting compared with BS yet are still classified as abnormal background patterns. In essence, EEG bursting patterns in the neonate stem from a triumvirate of BS, discontinuous (periodically alternating bursts and interbursts) and continuous activity patterns.
Additionally, early brain development depends upon spontaneously occurring, intermittent electrical activity that supports neuronal survival and sustains primary growth of brain networks. These bursting periods vary in their temporal evolution and spatial synchronicity across the cortex and are typically observed in preterm ages of 24-30 weeks. In the latter half of pregnancy, this electrical activity is highly sensitive to various endogenous and exogenous disturbances, creating clinical challenges in the acute care of preterm newborn infants. Despite advances in neonatal intensive care units (NICUs) worldwide, early preterm birth is still associated with a high risk of neurological morbidity (Back and Miller 2014). A major endeavor in NICUs worldwide is to complement early cardiorespiratory support with intensive brain monitoring, so as to identify early indices of cortical disturbance and guide appropriate clinical interventions.
Currently, preterm brain monitoring primarily involves visual assessment of electroencephalography (EEG) amplitudes (a.k.a. amplitude integrated EEG, aEEG; Hellstrom-Westas and Rosen, 2004; Olischar et al, 2004; Wikstrom et al, 2012) and the variation in EEG waveforms. These approaches toward EEG assessment in preterm infants, however, suffer from being qualitative, relying upon subjective appraisal, and being vulnerable to confounding factors arising from technical artefacts. Hence, there is an unmet need to derive cortical activity signatures of early brain function in preterm infants that are robust, objective, and based on firm statistical evidence.